Lecture 1: Introduction
Yale University
Staff
Econometrics vs. Statistics/Data Science
Econ 117 & 123 Sequence
Econ 123 in Detail
Field: Microeconometrics, Applied-Microeconometics;
Co-Editor of Journal of Applied Econometrics.
Fellow of the Econometric Society.
Founding member of the
International Association of Applied Econometrics.
Yale Economics Ph.d. student.
Fields:
Contact:
Staff
Econometrics vs. Statistics/Data Science
Econ 117 & 123 Sequence
Econ 123 in Detail
Second course in Economics dept sequence:
“Econometrics and Data Analysis”
If statistics is the “science of learning from data,”
then what is data science?
Is data science another name for applied statistics?
Samuelson, Koopmans, and Stone (1954):
the quantitative analysis of actual economic phenomena based on the concurrent development of theory and observation, related by appropriate methods of inference
Staff
Econometrics vs. Statistics/Data Science
Econ 117 & 123 Sequence
Econ 123 in Detail
Sequence in “Econometrics and Data Analysis’’
Sequence in “Econometrics and Data Analysis”
Sequence in “Econometrics and Data Analysis”
Staff
Econometrics vs. Statistics/Data Science
Econ 117 & 123 Sequence
Econ 123 in Detail
Covering additional, advanced topics including:
Go deeper on workflow, from acquiring data to presenting results.
Building upon the R coding you learned in Econ 117, e.g.,
In this course, we will use R,
Advantages of R over other options? Disadvantages?
Will relate to economic models of discrimination:
statistical- vs taste-based discrimination.
Pre-Req:
Econ 117: Introduction to Econometrics and Data Analysis.
What if you haven’t taken Econ 117?
Pre-Req:
Econ 117: Introduction to Econometrics and Data Analysis.
What if you haven’t taken Econ 117?
You should take Econ 117!
However, I will permit you to take Econ 123 if:
Lectures: Lecture slides will be posted on the course webpage, but are not designed as a substitute for attending lecture.
Labs: In-class labs where we live-code in R to analyze real data. The labs will be designed to directly help you with your problem sets.
You are expected to attend lectures and labs.
I will call on students.
| Assignments | Share of Course Grade |
|---|---|
| Online Quizzes | 10% |
| Problem Sets | 25% |
| Midterm | 20% |
| Final | 25% |
| Empirical Project | 20% |
Primarily empirical, based on academic research papers, though include some theoretical questions.
Should be turned in following the same problem set submission guidelines that you used in Econ 117.
Due dates are strict.1
The lowest problem set score will be dropped.
You may work in groups of up to four students on the problem sets.1
However, you must turn in your own assignment and indicate on your submission the other members of the group.
Deliverables:
Motivating example: labor force participation of women, based on Goldin (2006b)
Review causal inference, introduce models of discrimination.
Review inference, with applications to causal effects and discrimination.
Econ 123: Lecture 1